Senior Staff Software Engineer Capacity And Efficiency Engineering Jobs

Staff/Senior Engineer -Package Health System and Analytics — Fab 10A, Singapore. Apply via Workday.

Staff/Senior Engineer CE PYE (Physical Failure Analysis/Fault Isolation) — 2 Locations. Apply via Workday.

Staff/Senior Engineer, Operations Central Team, Manufacturing Technology Enablement Contamination Control — Hiroshima - Fab 15, Japan. Apply via Workday.

Staff/Senior Engineer, OCT MTE CC — Boise, ID - Main Site. Apply via Workday.

Staff / Senior Product Engineer - Advanced Analytics — MSB, Singapore. Apply via Workday.

Staff/Senior Engineer, PROCT FE Cost Excellence — 3 Locations. Apply via Workday.

Global Facilities Staff/Senior Engineer - Electrical FAC — Hiroshima - Fab 15, Japan. Apply via Workday.

FE CPIE Transformative Staff/Senior Engineer — 2 Locations. Apply via Workday.

We are looking for an experienced Senior or Staff Engineer for our SRE, InfraSec team, to guide the security of our cloud-based infrastructure. As a Staff SRE, you will be very hands-on technically while also mentoring a small team of SREs. The InfraSec team collaborates closely with other engineering teams to ensure that our infrastructure adheres to the highest security standards. They build essential security infrastructure and implement controls that reinforce the platform’s security posture. This is an SRE team, which means you can expect a highly hands-on approach, tackling the technical challenges of implementing large scale solutions.This team is deeply involved in the technical aspects of security and the nuances of its actual implementation. This role can sit in our New York City, Austin, Seattle or San Francisco offices on a hybrid basis, or it can be fully remote while working from a location based in either Eastern or Central time zones. Responsibilities: Cloud Security Design and Implementation: Help lead the design and deployment of security solutions for cloud platforms (AWS, Azure, GCP), including network and compute security, identity management, and cloud security posture management (CSPM) Automation and Monitoring: Build automated solutions for real-time security monitoring, logging, and alerting in cloud environments. Leverage native cloud services and third-party tools for runtime security monitoring and anomaly detection Security Tooling: Evaluate, implement, and manage cloud-native security tools and platforms for endpoint security, identity management (IAM), and CSPM Qualifications: Experience: 6+ years of experience in SRE, infrastructure engineering or similar role, with a strong focus on security work, with ideally 2+ years in a senior or staff engineering role Security Mindset: A comprehensive understanding of all facets of cloud environment security, spanning from foundational OS networking laye

Global Facilities and Construction South Asia Staff/Senior Engineer - Chemical — Fab 10A, Singapore. Apply via Workday.

Construction Ultra Pure Water & Waste Water Treatment Staff / Senior Engineer — Fab 10N/X, Singapore. Apply via Workday.

About the Role: We're hiring Senior and Staff Data Platform Engineers to join the Data Infrastructure teams in Toronto. Together these teams own the infrastructure that processes billions of events per day: Spark-on-Kubernetes, Flink and Kinesis pipelines, a multi-petabyte Delta Lake, a large-scale MemoryDB feature store, Databricks multi-environment operations, and the catalog and lifecycle systems that govern it. The team is small and senior. Each engineer owns major platform components: you design it, build it, and support it in production. This is a hybrid-role based out of our Toronto office. You must be willing to travel to our Toronto office two days/week. What You'll Do: Spark-on-Kubernetes — EKS-based compute platform for Spark workloads: cluster configuration, Pod Identity IAM, job environment setup, Kustomize overlays, and shadow canary validation Event ingestion — Rust services and Flink jobs processing billions of events per day over Kinesis; throughput, reliability, on-call response, and AI-assisted operational tooling to reduce toil Platform infrastructure — Terraform modules for environment provisioning, cross-account AWS IAM, ARC runner infrastructure, and CI/CD for data platform changes Feature store and ML compute — Flink-based real-time feature pipelines feeding a large-scale MemoryDB cluster; GPU capacity governance and Databricks multi-environment operations for ML training workloads Workflow orchestration and CDC — Airflow-based DAG deployment, change data capture pipeline operations, and data quality monitoring Your Background: 3+ years building and operating production data platform infrastructure at the cluster or platform level, across Spark, Flink, Kinesis, Kubernetes, or equivalent Deep experience in at least one of: Spark-on-K8s cluster operations, Rust-based data or systems engineering, Kubernetes platform engineering and IaC, or data catalog and governance tooling Production AWS experience or equivalent: EKS, S3, Kinesis, and mu

Who Are We? Postman is the world’s leading API platform, used by more than 45 million+ developers and 500,000 organizations, including 98% of the Fortune 500. Postman is helping developers and professionals across the globe build the API-first world by simplifying each step of the API lifecycle and streamlining collaboration—enabling users to create better APIs, faster. The company is headquartered in San Francisco and has offices in Boston, New York, Austin, Tokyo, London, and Bangalore - where Postman was founded. Postman is privately held, with funding from Battery Ventures, BOND, Coatue, CRV, Insight Partners, and Nexus Venture Partners. Learn more at postman.com or connect with Postman on X via @getpostman. P.S: We highly recommend reading The "API-First World" graphic novel to understand the bigger picture and our vision at Postman. About The Team We're looking for a self-motivated team member who craves a challenge, is obsessed with achieving key business objectives, and wants to work on one of the most loved developer products in the world. Product Marketing is responsible for developing crisp, highly differentiated, and compelling positioning and messaging for Postman and its services. We enable the revenue team to tell stories that educate customers about what is possible when they choose Postman to manage every API and service across their organization. As a Senior or Staff Product Marketing Manager, you will have the opportunity to create compelling content to help customers, especially platform engineers, and developers understand their use cases and value propositions, and build the right marketing programs to drive awareness, engagement, service adoption, and retention. This role sits in San Francisco, CA only. What You’ll Do Act as a product marketing lead for Postman features and services, and take ownership of the strategy to drive awareness and market penetration of key capabilities Work with engineering teams to distill key functional

Role Purpose We’re looking for a Staff/Senior Machine Learning Engineer with deep expertise in computer vision and biometrics to lead the design and scaling of face recognition systems in production. You’ll build and train models, and own ML systems end-to-end on AWS. The final job level for this role will be determined following the interview process. What You’ll Do Lead the design and development of computer vision systems for biometrics (face attributes, detection, quality, and recognition) Rigorous fairness analysis and benchmarking of biometric models across various datasets and operating conditions. Architect, train, and optimize models using PyTorch, Tensorflow, and/or JAX Own and evolve end-to-end ML pipelines, from data ingestion to deployment. Design automated pipelines (Airflow) for data ingestion and cleaning. You will be responsible for curating balanced training sets and generating synthetic data to address both quality and diversity gaps. Production Engineering: Own the path to production. Optimize models for low-latency inference (quantization, distillation, TensorRT/ONNX) and manage deployment on AWS. Mentor ML engineers, conduct code/design reviews, and drive technical best practices across the Computer Vision team. What We’re Looking For Experience: 5+ years of industry experience in Machine Learning, with at least 3 years dedicated to Biometrics or Face Analysis. Deep expertise in computer vision and biometrics, especially face recognition. Fairness & Ethics: You understand the sources of algorithmic bias in Computer Vision and have practical experience measuring and mitigating disparate impact. Strong Engineering: Expert proficiency in Python (both machine learning and vision libraries such as Pillow, OpenCV, PyTorch, etc). You write clean, modular, production-ready code. Systems Architecture: Experience designing end-to-end ML pipelines (Data to Train to Deploy) and working with workflow orchestrators like Airflow. Cloud Native: Hands-on ex

Machine Learning Engineer IV – (Computer Vision) We’re looking for a Staff/Senior Machine Learning Engineer with deep expertise in computer vision and biometrics to lead the design and scaling of face recognition systems in production. You’ll build and train models, and own ML systems end-to-end on AWS. The final job level for this role will be determined following the interview process. What You’ll Do Lead the design and development of computer vision systems for biometrics (face attributes, detection, quality, and recognition) Rigorous fairness analysis and benchmarking of biometric models across various datasets and operating conditions. Architect, train, and optimize models using PyTorch, Tensorflow, and/or JAX Own and evolve end-to-end ML pipelines, from data ingestion to deployment. Design automated pipelines (Airflow) for data ingestion and cleaning. You will be responsible for curating balanced training sets and generating synthetic data to address both quality and diversity gaps. Production Engineering: Own the path to production. Optimize models for low-latency inference (quantization, distillation, TensorRT/ONNX) and manage deployment on AWS. Mentor ML engineers, conduct code/design reviews, and drive technical best practices across the Computer Vision team. What We’re Looking For Strong industry experience in Machine Learning, dedicated to Biometrics or Face Analysis. Deep expertise in computer vision and biometrics, especially face recognition. Fairness & Ethics: You understand the sources of algorithmic bias in Computer Vision and have practical experience measuring and mitigating disparate impact. Strong Engineering: Expert proficiency in Python (both machine learning and vision libraries such as Pillow, OpenCV, PyTorch, etc). You write clean, modular, production-ready code. Systems Architecture: Experience designing end-to-end ML pipelines (Data to Train to Deploy) and working with workflow orchestrators like Airflow. Cloud Native: Hands-on exper